Fusion Domain-Adaptation CNN Driven by Images and Vibration Signals for Fault Diagnosis of Gearbox Cross-Working Conditions

The vibration signal of gearboxes contains abundant fault information, which can be used for condition monitoring. However, vibration signal is ineffective for some non-structural failures. In order to resolve this dilemma, infrared thermal images are introduced to combine with vibration signals via fusion domain-adaptation convolutional neural network (FDACNN), which can diagnose both structural and non-structural failures under various working conditions. First, the measured raw signals are converted into frequency and squared envelope spectrum to characterize the health states of the gearbox. Second, the sequences of the frequency and squared envelope spectrum are arranged into two-dimensional format, which are combined with infrared thermal images to form fusion data. Finally, the adversarial network is introduced to realize the state recognition of structural and non-structural faults in the unlabeled target domain. An experiment of gearbox test rigs was used for effectiveness validation by measuring both vibration and infrared thermal images. The results suggest that the proposed FDACNN method performs best in cross-domain fault diagnosis of gearboxes via multi-source heterogeneous data compared with the other four methods.

Assessment of IsPETase-Assisted Depolymerization of Terephthalate Aromatic Polyesters and the Effect of the Thioredoxin Fusion Domain

Terephthalate polyesters such as poly(ethylene terephthalate) (PET) have been massively produced over the last few decades due to their attractive properties in multiple applications. However, due to their limited biodegradability, they have accumulated in landfills and oceans, posing an environmental threat. Enzymatic recycling technologies are predicted to generate long-term socioeconomic benefits. In the present work, we compared the IsPETase (from Ideonella sakaiensis 201-F6) activity on a series of polyesters, including poly(butylene) terephthalate (PBT), poly(hexamethylene) terephthalate (PHT) and Akestra™, with PET. The IsPETase showed remarkable activity toward PET (39% degradation of the original polyester) that was higher than that toward Akestra™ (0.13%), PBT (0.25%) and PHT (0.13%) after 72 h. Thus, based on experimental data and computational analysis, we report insights into IsPETase activity on a series of terephthalate-based polyesters. Aside from that, the fusion domain (Trx) effect in the production and activity of a recombinant Trx-IsPETase is reported.

Strikingly different roles of SARS-CoV-2 fusion peptides uncovered by neutron scattering

Coronavirus disease-2019 (COVID-19), a lethal respiratory illness caused by the coronavirus SARS-CoV-2, emerged in the end of 2019 and has since spread aggressively across the globe. A thorough understanding of the molecular mechanisms of cellular infection by coronaviruses is therefore of utmost importance. A critical stage in infection is the fusion between viral and host membranes. Here, we present a detailed investigation of the role of the SARS-CoV-2 Spike protein, and the influence of calcium and cholesterol, in this fusion process. Structural information from specular neutron reflectometry and small angle neutron scattering, complemented by dynamics information from quasi-elastic and spin-echo neutron spectroscopy, revealed strikingly different functions encoded in the Spike fusion domain. Calcium drives the N-terminal of the Spike fusion domain to fully cross the host plasma membrane. Removing calcium however re-orients the protein to the lipid leaflet in contact with the virus, leading to significant changes in lipid fluidity and rigidity. In conjunction with other regions of the fusion domain which are also positioned to bridge and dehydrate viral and host membranes, the molecular events leading to cell entry by SARS-CoV-2 are proposed.

A Distributed Fusion Framework of Multispectral and Panchromatic Images Based on Residual Network

Remote sensing images have been widely applied in various industries; nevertheless, the resolution of such images is relatively low. Panchromatic sharpening (pan-sharpening) is a research focus in the image fusion domain of remote sensing. Pan-sharpening is used to generate high-resolution multispectral (HRMS) images making full use of low-resolution multispectral (LRMS) images and panchromatic (PAN) images. Traditional pan-sharpening has the problems of spectral distortion, ringing effect, and low resolution. The convolutional neural network (CNN) is gradually applied to pan-sharpening. Aiming at the aforementioned problems, we propose a distributed fusion framework based on residual CNN (RCNN), namely, RDFNet, which realizes the data fusion of three channels. It can make the most of the spectral information and spatial information of LRMS and PAN images. The proposed fusion network employs a distributed fusion architecture to make the best of the fusion outcome of the previous step in the fusion channel, so that the subsequent fusion acquires much more spectral and spatial information. Moreover, two feature extraction channels are used to extract the features of MS and PAN images respectively, using the residual module, and features of different scales are used for the fusion channel. In this way, spectral distortion and spatial information loss are reduced. Employing data from four different satellites to compare the proposed RDFNet, the results of the experiment show that the proposed RDFNet has superior performance in improving spatial resolution and preserving spectral information, and has good robustness and generalization in improving the fusion quality.

Cross-reactive CD4+ T cells enhance SARS-CoV-2 immune responses upon infection and vaccination

While evidence for pre-existing SARS-CoV-2-cross-reactive CD4+ T cells in unexposed individuals is increasing, their functional significance remains unclear. Here, we comprehensively determined SARS-CoV-2-cross-reactivity and human coronavirus-reactivity in unexposed individuals. SARS-CoV-2-cross-reactive CD4+ T cells were ubiquitous, but their presence decreased with age. Within the spike glycoprotein fusion domain, we identified a universal immunodominant coronavirus-specific peptide epitope (iCope). Pre-existing spike- and iCope-reactive memory T cells were efficiently recruited into mild SARS-CoV-2 infections and their abundance correlated with higher IgG titers. Importantly, the cells were also reactivated after primary BNT162b2 COVID-19 mRNA vaccination in which their kinetics resembled that of secondary immune responses. Our results highlight the functional importance of pre-existing spike-cross-reactive T cells in SARS-CoV-2 infection and vaccination. Abundant spike-specific cross-immunity may be responsible for the unexpectedly high efficacy of current vaccines even with single doses and the high rate of asymptomatic/mild infection courses.

Enhanced Cholesterol-dependent Hemifusion by Internal Fusion Peptide 1 of SARS Coronavirus-2 Compared to its N-terminal Counterpart

ABSTRACTMembrane fusion is an important step for the entry of the lipid-sheathed viruses into the host cells. The fusion process is being carried out by fusion proteins present in the viral envelope. The class I viruses contains a 20-25 amino acid sequence at its N-terminal of the fusion domain, which is instrumental in fusion, and is termed as ‘fusion peptide’. However, Severe Acute Respiratory Syndrome Coronavirus (SARS) coronaviruses contain more than one fusion peptide sequences. We have shown that the internal fusion peptide 1 (IFP1) of SARS-CoV is far more efficient than its N-terminal counterpart (FP) to induce hemifusion between small unilamellar vesicles. Moreover, the ability of IFP1 to induce hemifusion formation increases dramatically with growing cholesterol content in the membrane. Interestingly, IFP1 is capable of inducing hemifusion, but fails to open pore.

Drug Repurposing Commonly Against Dengue Virus Capsid and SARS-CoV-2 Nucleocapsid: An in Silico Approach

<p>In the middle of SARS-CoV-2 pandemic, dengue virus (DENV) is giving a silent warning as the season approaches nearer. There is no specific antiviral against DENV for use in the clinics. Thus, considering these facts we can potentially face both these viruses together increasing the clinical burden. The search for anti-viral drugs against SARS-CoV-2 is in full swing and repurposing of already ‘in-use’ drugs against other diseases or COVID-19 has drawn significant attention. Earlier we had reported few FDA approved anti-viral and anti-microbial drugs that could be tested against SARS-CoV-2 nucleocapsid assembly. We explored the possibility of interactions of these shortlisted drugs against SARS-CoV2 with Dengue virus proteins. Here we report three FDA approved drugs (Daclatasvir, Letermovir and Rifampicin) that were seen to be docking onto the SARS-CoV-2 nucleocapsid RNA binding domain, also docking strongly with DENV capsid protein on the RNA binding site and/or the capsid’s membrane fusion domain. Thus, the present study proposes these three drugs as common antiviral candidates against both SARS-CoV-2 and DENV.</p>